公开(公告)号：US20210012160A1

公开(公告)日：2021-01-14

申请号：US17035401

申请日：2020-09-28

Applicant: Lunit Inc.

Inventor： Jongchan PARK ,  Donggeun YOO

IPC: G06K9/62 ,  G16H30/20 ,  G06T7/70 ,  G06T7/00

Abstract: This disclosure relates to a computerized method to perform a machine learning on a relationship between medical images and metadata using a neural network and acquiring metadata by applying a machine learning model to medical images, and a method thereof. The apparatus and method may include training a prediction model for predicting metadata of medical images based on multiple medical images for learning and metadata matched with each of multiple medical images and predicting metadata of input medical image.

公开(公告)号：US10825178B1

公开(公告)日：2020-11-03

申请号：US16707830

申请日：2019-12-09

Applicant: Lunit Inc.

Inventor： Nayoung Jeong ,  Ki Hwan Kim ,  Minhong Jang

IPC: G06T7/00 ,  G16H30/20 ,  G16H30/40 ,  G06N3/04 ,  G06N3/08 ,  G06N20/00

Abstract: Provided are a computerized image interpretation method and a device for analyzing a medical image. The image interpretation method may include receiving, at a processor, a medical image, and receiving report information including a healthcare worker's judgement result of the medical image. The method may also include generating, at the processor, result information representing correspondence between first lesion information, which is related to a lesion in the medical image acquired on the basis of the medical image, and second lesion information, which is related to a lesion in the medical image acquired on the basis of the report information, by applying the first lesion information and the second lesion information to a third analysis model. The method may further include outputting, at the processor, the result information.

公开(公告)号：US20200302290A1

公开(公告)日：2020-09-24

申请号：US16676694

申请日：2019-11-07

Applicant: Lunit Inc.

Inventor： Hyun Jae LEE

IPC: G06N3/08 ,  G06N20/00 ,  G06T3/00 ,  G06F17/18

Abstract: A method of recalibrating a feature data of each channel generated by a convolution layer of a convolution neural network is provided. According to some embodiments, since an affine transformation is applied to the feature data of each channel independently of the feature data of the other channel, the overall number of parameters defining the affine transformation is minimized. As a result, the amount of computations required in performing the feature data recalibration can be reduced.

公开(公告)号：US20180144209A1

公开(公告)日：2018-05-24

申请号：US15378039

申请日：2016-12-14

Applicant: Lunit Inc.

Inventor： Hyo Eun KIM ,  Sang Heum HWANG

IPC: G06K9/46 ,  G06T7/00 ,  G06N3/08 ,  G06N3/04 ,  G06F19/00

CPC classification number: G06K9/4671 ,  G06N3/04 ,  G06N3/0454 ,  G06N3/08 ,  G06T7/0012 ,  G06T2207/10004 ,  G06T2207/20081 ,  G06T2207/20084 ,  G06T2207/30096 ,  G16H50/20

Abstract: Provided are an object recognition method and apparatus which determine an object of interest included in a recognition target image using a trained machine learning model and determine an area in which the object of interest is located in the recognition target image. The object recognition method based on weakly supervised learning, performed by an object recognition apparatus, includes extracting a plurality of feature maps from a training target image given classification results of objects of interest, generating an activation map for each of the objects of interest by accumulating the feature maps, calculating a representative value of each of the objects of interest by aggregating activation values included in a corresponding activation map, determining an error by comparing classification results determined using the representative value of each of the objects of interest with the given classification results and updating a CNN-based object recognition model by back-propagating the error.

公开(公告)号：US20250166192A1

公开(公告)日：2025-05-22

申请号：US19034933

申请日：2025-01-23

Applicant: LUNIT INC.

Inventor： Donggeun YOO

IPC: G06T7/00 ,  G06V10/22 ,  G06V10/774 ,  G16H30/40 ,  G16H70/60

Abstract: A method for parallel processing a digitally scanned pathology image is performed by a plurality of processors and includes performing, by a first processor, a first operation of generating a first batch from a first set of patches extracted from a digitally scanned pathology image and providing the generated first batch to a second processor, performing, by the first processor, a second operation of generating a second batch from a second set of patches extracted from the digitally scanned pathology image and providing the generated second batch to the second processor, and performing, by the second processor, a third operation of outputting a first analysis result from the first batch by using a machine learning model, with at least part of time frame for the second operation performed by the first processor overlapping at least part of time frame for the third operation performed by the second processor.

公开(公告)号：US20250149150A1

公开(公告)日：2025-05-08

申请号：US19017915

申请日：2025-01-13

Applicant: LUNIT INC,

Inventor： Jeong Seok KANG ,  Jae Hong AUM ,  Dong Geun YOO ,  Tai Won CHUNG

IPC: G16H30/40 ,  G16H10/40

Abstract: A computing apparatus includes: at least one memory; and at least one processor, wherein the processor generates quantitative information regarding at least one cell included in a region of interest of a pathological slide image by analyzing the pathological slide image, generates qualitative information regarding at least one tissue included in the pathological slide image by analyzing the pathological slide image, and controls a display apparatus to output at least one of the quantitative information and the qualitative information on the pathological slide image according to a manipulation of a user.

公开(公告)号：US20250132021A1

公开(公告)日：2025-04-24

申请号：US18989313

申请日：2024-12-20

Applicant: Lunit Inc.

Inventor： Kyoung Won LEE ,  Kyung Hyun PAENG

IPC: G16H30/40 ,  G06F18/21 ,  G06F40/169 ,  G06N3/08 ,  G06Q10/0631 ,  G06Q10/0639 ,  G06T7/00 ,  G06V10/22 ,  G06V10/774 ,  G06V10/776 ,  G06V10/778 ,  G16H10/40 ,  G16H30/20 ,  G16H40/20

Abstract: A computing device obtains information about a medical slide image, and determines a dataset type of the medical slide image and a panel of the medical slide image. The computing device assigns to an annotator account, an annotation job defined by at least the medical slide image, the determined dataset type, an annotation task, and a patch that is a partial area of the medical slide image. The annotation task includes the determined panel, and the panel is designated as one of a plurality of panels including a cell panel, a tissue panel, and a structure panel. The dataset type indicates a use of the medical slide image and is designated as one of a plurality of uses including a training use of a medical learning model and a validation use of the machine learning model.

公开(公告)号：US20250124577A1

公开(公告)日：2025-04-17

申请号：US18986988

申请日：2024-12-19

Applicant: Lunit Inc.

Inventor： Nayoung JEONG ,  Ki Hwan KIM ,  Minhong JANG

IPC: G06T7/00 ,  G06N3/045 ,  G06N3/08 ,  G06N20/00 ,  G16H30/20 ,  G16H30/40

Abstract: Provided are a computerized image interpretation method and a device for analyzing a medical image. The image interpretation method may include receiving, at a processor, a medical image, and receiving report information including a healthcare worker's judgement result of the medical image. The method may also include generating, at the processor, result information representing correspondence between first lesion information, which is related to a lesion in the medical image acquired on the basis of the medical image, and second lesion information, which is related to a lesion in the medical image acquired on the basis of the report information, by applying the first lesion information and the second lesion information to a third analysis model. The method may further include outputting, at the processor, the result information.

公开(公告)号：US12266447B2

公开(公告)日：2025-04-01

申请号：US17502304

申请日：2021-10-15

Applicant: LUNIT INC.

Inventor： Donggeun Yoo ,  Jeong Hoon Lee ,  Kyunghyun Paeng

IPC: G16H50/20 ,  G06T7/00 ,  G16H10/60 ,  G16H50/70

Abstract: A method for generating a medical prediction related to a biomarker from medical data is provided, which includes obtaining medical data associated with a patient, determining a region of interest in the medical data, extracting one or more features associated with the medical data based on the region of interest, and generating a medical prediction for the patient based on the extracted one or more features.

公开(公告)号：US12217853B2

公开(公告)日：2025-02-04

申请号：US17720549

申请日：2022-04-14

Applicant: Lunit Inc.

Inventor： Kyoung Won Lee ,  Kyung Hyun Paeng

IPC: G16H30/40 ,  G06F18/21 ,  G06F40/169 ,  G06N3/08 ,  G06N20/00 ,  G06Q10/0631 ,  G06Q10/0639 ,  G06T7/00 ,  G06V10/22 ,  G06V10/774 ,  G06V10/776 ,  G06V10/778 ,  G16H10/40 ,  G16H30/20 ,  G16H40/20 ,  G16H50/20

Abstract: A computing device obtains information about a medical slide image, and determines a dataset type of the medical slide image and a panel of the medical slide image. The computing device assigns to an annotator account, an annotation job defined by at least the medical slide image, the determined dataset type, an annotation task, and a patch that is a partial area of the medical slide image. The annotation task includes the determined panel, and the panel is designated as one of a plurality of panels including a cell panel, a tissue panel, and a structure panel. The dataset type indicates a use of the medical slide image and is designated as one of a plurality of uses including a training use of a medical learning model and a validation use of the machine learning model.